Pipeline

Multilingual dubbing pipeline

Turns a Chinese video into English and Tamil narration that stays in sync with the picture.

pradeep.build / build reportMedia & content · Pipeline

What it does

An end-to-end pipeline: speech to text, scripts written against timestamps, a cloned English voice, Tamil text to speech, and automatic retiming of the video so every line lands on its scene.

The problem

Dubbing a long video by hand means transcribing, translating, recording and editing every scene. Machine translation alone drifts out of sync and reads badly when spoken.

Approach

Scripts are written per timestamped block, so each line has a time budget. The English and Tamil voices come from AI voice models, chosen after testing four voice engines. When a line runs long or short, the video block is stretched or trimmed instead of rushing the voice.

  • Input
  • AI step
  • Rules or code
  • Person decides
  • Result
How it flows

Screens

Swipe sideways to see the whole screen.

Client work is shown under confidentiality agreements: no client names, and screens are recreated with sample data.

Stack

  • Gemini API
  • AI voice models
  • Video editing

Impact

80 to 90%lower cost per finished minute than studio dubbing
Hoursper language instead of the usual 2 to 6 weeks

Typical for systems like this.

Next buildMulti-platform publishing automation Process automation · Media & content
Pradeep Loganathan

What should we build next?

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